{"id":"https://openalex.org/W3165686988","doi":"https://doi.org/10.1109/isbi48211.2021.9434165","title":"Exploring Instance-Level Uncertainty for Medical Detection","display_name":"Exploring Instance-Level Uncertainty for Medical Detection","publication_year":2021,"publication_date":"2021-04-13","ids":{"openalex":"https://openalex.org/W3165686988","doi":"https://doi.org/10.1109/isbi48211.2021.9434165","mag":"3165686988"},"language":"en","primary_location":{"id":"doi:10.1109/isbi48211.2021.9434165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi48211.2021.9434165","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031064605","display_name":"Jiawei Yang","orcid":"https://orcid.org/0000-0002-5129-0103"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jiawei Yang","raw_affiliation_strings":["Electrical and Computer Engineering, University of California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, University of California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100390856","display_name":"Yuan Liang","orcid":"https://orcid.org/0000-0002-1861-4479"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuan Liang","raw_affiliation_strings":["Electrical and Computer Engineering, University of California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, University of California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100446997","display_name":"Yao Zhang","orcid":"https://orcid.org/0000-0002-8759-4811"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Zhang","raw_affiliation_strings":["Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China","University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019008241","display_name":"Weinan Song","orcid":"https://orcid.org/0000-0002-7464-1551"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weinan Song","raw_affiliation_strings":["Electrical and Computer Engineering, University of California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, University of California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100366662","display_name":"Kun Wang","orcid":"https://orcid.org/0000-0002-4794-2359"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kun Wang","raw_affiliation_strings":["Electrical and Computer Engineering, University of California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, University of California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008695429","display_name":"Lei He","orcid":"https://orcid.org/0000-0002-5266-3805"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lei He","raw_affiliation_strings":["Electrical and Computer Engineering, University of California, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, University of California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5031064605"],"corresponding_institution_ids":["https://openalex.org/I161318765"],"apc_list":null,"apc_paid":null,"fwci":0.5498,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.65609099,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"448","last_page":"452"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7749114036560059},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.7746316194534302},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.7133595943450928},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.6891350746154785},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5876778364181519},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5311967730522156},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5229150056838989},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47678685188293457},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4640893340110779},{"id":"https://openalex.org/keywords/measurement-uncertainty","display_name":"Measurement uncertainty","score":0.42019107937812805},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4195757210254669},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3545262813568115},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3294096291065216},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3111116290092468},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2632550299167633},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13214048743247986}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7749114036560059},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.7746316194534302},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.7133595943450928},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.6891350746154785},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5876778364181519},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5311967730522156},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5229150056838989},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47678685188293457},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4640893340110779},{"id":"https://openalex.org/C137209882","wikidata":"https://www.wikidata.org/wiki/Q1403517","display_name":"Measurement uncertainty","level":2,"score":0.42019107937812805},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4195757210254669},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3545262813568115},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3294096291065216},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3111116290092468},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2632550299167633},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13214048743247986},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi48211.2021.9434165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi48211.2021.9434165","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W582134693","https://openalex.org/W2322371438","https://openalex.org/W2462906003","https://openalex.org/W2584017349","https://openalex.org/W2600383743","https://openalex.org/W2769848455","https://openalex.org/W2774764242","https://openalex.org/W2800755727","https://openalex.org/W2887976372","https://openalex.org/W2897451575","https://openalex.org/W2902424921","https://openalex.org/W2927565600","https://openalex.org/W2936835627","https://openalex.org/W2951965145","https://openalex.org/W2962677013","https://openalex.org/W2963351448","https://openalex.org/W2963777800","https://openalex.org/W2964059111","https://openalex.org/W2968924835","https://openalex.org/W2971561076","https://openalex.org/W3016191673","https://openalex.org/W3031149076","https://openalex.org/W3037156242","https://openalex.org/W3106917810","https://openalex.org/W6617145748","https://openalex.org/W6718836005","https://openalex.org/W6735443497","https://openalex.org/W6747071220","https://openalex.org/W6756341756","https://openalex.org/W6760785693","https://openalex.org/W6761320662","https://openalex.org/W6785778888"],"related_works":["https://openalex.org/W4237171675","https://openalex.org/W3036286480","https://openalex.org/W4287027631","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W4390524233"],"abstract_inverted_index":{"The":[0],"ability":[1],"of":[2,59,129,132,169],"deep":[3],"learning":[4],"to":[5,29,56,68,123,145,157,164],"predict":[6],"with":[7,73],"uncertainty":[8,27,39,79,139],"is":[9],"recognized":[10],"as":[11],"key":[12],"for":[13,93],"its":[14,46],"adoption":[15],"in":[16,41,177],"clinical":[17],"routines.":[18],"Moreover,":[19,134],"performance":[20,156],"gain":[21],"has":[22,35,51],"been":[23,52],"enabled":[24],"by":[25,125],"modeling":[26],"according":[28],"empirical":[30],"evidences.":[31],"While":[32],"previous":[33],"work":[34],"widely":[36],"discussed":[37],"the":[38,57,118,137,147,155,167],"estimation":[40],"segmentation":[42],"and":[43,84,110,151],"classification":[44],"tasks,":[45],"application":[47],"on":[48,97],"bounding-box-based":[49],"detection":[50,71,96],"limited,":[53],"mainly":[54],"due":[55],"challenge":[58],"bounding":[60],"box":[61],"aligning.":[62],"In":[63],"this":[64],"work,":[65],"we":[66,135],"explore":[67],"augment":[69],"a":[70,100,127],"CNN":[72],"two":[74],"different":[75],"bounding-box-level":[76],"(or":[77],"instance-level)":[78],"estimates,":[80],"i.e.,":[81],"predictive":[82],"variance":[83],"Monte":[85],"Carlo":[86],"(MC)":[87],"sample":[88],"variance.":[89],"Experiments":[90],"are":[91,162],"conducted":[92],"lung":[94],"nodule":[95,160],"LUNA16":[98],"dataset,":[99],"task":[101],"where":[102],"significant":[103],"semantic":[104],"ambiguities":[105],"can":[106,152,174],"exist":[107],"between":[108],"nodules":[109],"non-nodules.":[111],"Results":[112],"show":[113,136],"that":[114],"our":[115,170],"method":[116],"improves":[117],"evaluating":[119],"score":[120],"from":[121],"84.57%":[122],"88.86%":[124],"utilizing":[126],"combination":[128],"both":[130],"types":[131],"variances.":[133],"generated":[138],"enables":[140],"superior":[141],"operating":[142],"points":[143],"compared":[144],"using":[146],"probability":[148],"threshold":[149],"only,":[150],"further":[153,165],"boost":[154],"89.52%.":[158],"Example":[159],"detections":[161],"visualized":[163],"illustrate":[166],"advantages":[168],"method.":[171],"Our":[172],"implementation":[173],"be":[175],"found":[176],"https://git.io/JTwhe.":[178]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}